1. Field of the Invention
The present invention relates to an analog-to-digital (AD) conversion apparatus, an AD conversion method, and an electronic device.
2. Related Art
Sampling methods used in AD converter are classified broadly into a type of executing sampling with Nyquist frequency and an oversampling type of executing sampling with frequency higher than Nyquist frequency. The oversampling type is intended to enhance a resolution even using an AD converter with a low resolution. Σ-Δ (sigma-delta) type sampling is exemplified as one of the common sampling methods at this time.
The oversampling type AD converter obtains an intermediate value of output codes by averaging a plurality of AD conversion results sampled with sampling rate higher than the Nyquist frequency. The intermediate value is obtained with various techniques. The original form to obtain the intermediate value utilizes white noise as dither noise.
The principle to obtain the intermediate value is that the intermediate value of output codes from the AD converter can be obtained by averaging the plurality of the AD conversion results when outputs from the AD converter on each conversion take different values influenced by noise (that is, when outputs keep flickering). This principle has the premise that an average of the noise which causes the flickering is zero, that an effective value of the noise level to the resolution of the AD converter takes from ⅓ LSB (Least Significant Bit) to several LSBs, and that the noise has sufficiently broad bandwidth so that a different result can be obtained on each sampling.    Patent Document 1: JP-A-2010-11906
However, it is often difficult for the AD converter with the low resolution to obtain effects of oversampling since its noise level is far lower than the amplitude of 1 LSB of the AD converter. It is not only technically difficult but also costly to generate white noise with appropriate bandwidth intendedly and stably. Thermal noise of a resistance is widely understood as an example of white noise. The noise voltage vn is represented as vn=(4kTRΔf)1/2(k: Boltzmann constant, T: temperature, R: resistance, Δf bandwidth of noise). Even if R=1 MΩ, T=300 K, and M=1 MHz, the noise voltage to be obtained is 0.13 mVrms at most. When a 10 bit AD converter has an input voltage range from 0 V to 3 V, the resolution of the 10 bit AD converter is approximately 3 mV/LSB. As a result, the thermal noise should be amplified several dozen-fold for practical purposes.
The frequency band of white noise should be sufficiently higher than signal frequency. If a negative feedback circuit including an operational amplifier for noise amplification is utilized, high frequency-response property corresponding to gain of the operational amplifier is required. Furthermore, particularly low equivalent input noise of the operational amplifier is required for utilizing thermal noise as white noise for sampling. An operational amplifier which satisfies such requirements is far better performing and expensive than a general buffer amplifier placed before the AD converter for processing an original signal. Moreover, an actual resistive element generates not only theoretical thermal noise but also large 1/f noise, a noise level of the thermal noise may vary depending on temperature, and environmental noise may be superimposed on the thermal noise. Accordingly, it is difficult to generate large amounts of noise intentionally and stably.
Noise of a Zener diode similar to white noise might be adopted as the sampling noise. However, the Zener diode has problems in that it consumes huge amounts of current, its inter-individual difference is large, and its temperature property is worse than that of the resistance.
In another problem, in the oversampling with dither noise, if that it is required for improving a resolution of sampling to increase the number of sampling in accordance with the number of bits.
The Σ-Δ type sampling, which is another type of oversampling, shortens measurement time for sampling in comparison with the oversampling with the dither noise, meanwhile the Σ-Δ type sampling requires massive and complex digital processing. The Σ-Δ type sampling prevails due to current miniaturization technologies. However, semiconductor products specialized for the Σ-Δ type sampling remain expensive. If the digital processing to be executed by hardware in the semiconductor products is executed by software, only a signal having a frequency lower than one several dozenth of clock frequency can be processable. Therefore, it is difficult to execute the Σ-Δ type sampling at high frequency.